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-rw-r--r--README10
-rw-r--r--acarp.css12
-rw-r--r--demo-beamer.md8
-rw-r--r--demo-standard.md8
4 files changed, 31 insertions, 7 deletions
diff --git a/README b/README
index 8f69673..9f18db3 100644
--- a/README
+++ b/README
@@ -54,6 +54,16 @@ Text content
</div>
```
+### `cite` - Citation/Attribution
+```markdown
+---
+### Slide Title
+
+Your content here
+
+<div class="cite">[Author et al., Year]</div>
+```
+
### Default - Single Column
```markdown
---
diff --git a/acarp.css b/acarp.css
index 6395e52..98363d7 100644
--- a/acarp.css
+++ b/acarp.css
@@ -310,6 +310,16 @@ section p > img:only-child {
margin: 0 auto;
}
+/* Citation utility - bottom left corner */
+.cite {
+ position: absolute;
+ bottom: 30px;
+ left: var(--padding);
+ font-size: 0.7em;
+ color: #888888;
+ opacity: 0.9;
+}
+
/* ============================================================================
LAYOUT: title
@@ -377,7 +387,7 @@ section.layout-2col {
grid-template-areas:
"title title"
"left right"
- "footer footer";
+ "buffer buffer";
gap: 2em;
padding: 0;
height: 100%;
diff --git a/demo-beamer.md b/demo-beamer.md
index 9a5fec9..db2efa7 100644
--- a/demo-beamer.md
+++ b/demo-beamer.md
@@ -62,16 +62,18 @@ A minimal, grid-based setup for Marp presentations:
The TF-IDF model for term weighting:
-$$\text{tf-idf}(t, d, D) = \text{tf}(t, d) \times \text{idf}(t, D)$$
+$\text{tf-idf}(t, d, D) = \text{tf}(t, d) \times \text{idf}(t, D)$
Where term frequency is:
-$$\text{tf}(t, d) = \frac{f_{t,d}}{\sum_{t'\in d} f_{t',d}}$$
+$\text{tf}(t, d) = \frac{f_{t,d}}{\sum_{t'\in d} f_{t',d}}$
And inverse document frequency:
-$$\text{idf}(t, D) = \log \frac{|D|}{|\{d \in D : t \in d\}|}$$
+$\text{idf}(t, D) = \log \frac{|D|}{|\{d \in D : t \in d\}|}$
The 4:3 format provides better vertical space for multi-line equations.
+<div class="cite">[Sparck Jones, 1972]</div>
+
---
### Code Examples
diff --git a/demo-standard.md b/demo-standard.md
index 20d887f..1e1ea75 100644
--- a/demo-standard.md
+++ b/demo-standard.md
@@ -72,13 +72,15 @@ A minimal, grid-based setup for Marp presentations:
The TF-IDF model for term weighting:
-$$\text{tf-idf}(t, d, D) = \text{tf}(t, d) \times \text{idf}(t, D)$$
+$\text{tf-idf}(t, d, D) = \text{tf}(t, d) \times \text{idf}(t, D)$
Where term frequency is:
-$$\text{tf}(t, d) = \frac{f_{t,d}}{\sum_{t'\in d} f_{t',d}}$$
+$\text{tf}(t, d) = \frac{f_{t,d}}{\sum_{t'\in d} f_{t',d}}$
And inverse document frequency:
-$$\text{idf}(t, D) = \log \frac{|D|}{|\{d \in D : t \in d\}|}$$
+$\text{idf}(t, D) = \log \frac{|D|}{|\{d \in D : t \in d\}|}$
+
+<div class="cite">[Sparck Jones, 1972]</div>
---